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Article: Variations in the Effects of Landscape Patterns on the Urban Thermal Environment during Rapid Urbanization (1990–2020) in Megacities

TitleVariations in the Effects of Landscape Patterns on the Urban Thermal Environment during Rapid Urbanization (1990–2020) in Megacities
Authors
Keywordsurban thermal environment
landscape pattern
megacity
spatiotemporal analysis
urbanization stage
Issue Date2021
PublisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/remotesensing/
Citation
Remote Sensing, 2021, v. 13, p. article no. 3415 How to Cite?
AbstractDeterioration of the urban thermal environment, especially in megacities with intensive populations and high densities of impervious surfaces, is a global issue resulting from rapid urbanization. The effects of landscape patterns on the urban thermal environment within a single area or single period have been well documented. Few studies, however, have explored whether the effects can be adapted to various cities at different urbanization stages. This paper investigated the variations of these effects in the five largest and highly urbanized megacities of China from 1990 to 2020 using various geospatial approaches, including concentric buffer analysis, correlation analysis, and hierarchical ridge regression models. The results indicated that the effects of landscape patterns on the urban thermal environment were greatly variable at different urbanization stages. Although landscape composition was more important than landscape configuration in determining the urban thermal environment, the standard coefficients of composition metrics continuously decreased from 1990 to 2020. However, configuration metrics, such as patch density, edge density, and shape complexity, could affect the land surface temperature (LST) to a larger extent at the highly urbanized stage. The urbanization process could also affect the cooling effect of urban green space. At the initial stage of rapid urban expansion in approximately 2000, urban green space explained the most variation in LST, with a value as high as 10%. To maximize the cooling effect, the spatial arrangement of urban green space should be highlighted in the region that was 10–15 km from the city center, where the mean LST experienced a significant decline. These results may provide deeper insights into improving the urban thermal environment by targeted strategies in optimizing landscape patterns for areas at different urbanization stages.
Persistent Identifierhttp://hdl.handle.net/10722/305621
ISSN
2021 Impact Factor: 5.349
2020 SCImago Journal Rankings: 1.285
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYe, H-
dc.contributor.authorLi, Z-
dc.contributor.authorZhang, N-
dc.contributor.authorLeng, X-
dc.contributor.authorMeng, D-
dc.contributor.authorZheng, J-
dc.contributor.authorLi, Y-
dc.date.accessioned2021-10-20T10:11:59Z-
dc.date.available2021-10-20T10:11:59Z-
dc.date.issued2021-
dc.identifier.citationRemote Sensing, 2021, v. 13, p. article no. 3415-
dc.identifier.issn2072-4292-
dc.identifier.urihttp://hdl.handle.net/10722/305621-
dc.description.abstractDeterioration of the urban thermal environment, especially in megacities with intensive populations and high densities of impervious surfaces, is a global issue resulting from rapid urbanization. The effects of landscape patterns on the urban thermal environment within a single area or single period have been well documented. Few studies, however, have explored whether the effects can be adapted to various cities at different urbanization stages. This paper investigated the variations of these effects in the five largest and highly urbanized megacities of China from 1990 to 2020 using various geospatial approaches, including concentric buffer analysis, correlation analysis, and hierarchical ridge regression models. The results indicated that the effects of landscape patterns on the urban thermal environment were greatly variable at different urbanization stages. Although landscape composition was more important than landscape configuration in determining the urban thermal environment, the standard coefficients of composition metrics continuously decreased from 1990 to 2020. However, configuration metrics, such as patch density, edge density, and shape complexity, could affect the land surface temperature (LST) to a larger extent at the highly urbanized stage. The urbanization process could also affect the cooling effect of urban green space. At the initial stage of rapid urban expansion in approximately 2000, urban green space explained the most variation in LST, with a value as high as 10%. To maximize the cooling effect, the spatial arrangement of urban green space should be highlighted in the region that was 10–15 km from the city center, where the mean LST experienced a significant decline. These results may provide deeper insights into improving the urban thermal environment by targeted strategies in optimizing landscape patterns for areas at different urbanization stages.-
dc.languageeng-
dc.publisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/remotesensing/-
dc.relation.ispartofRemote Sensing-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjecturban thermal environment-
dc.subjectlandscape pattern-
dc.subjectmegacity-
dc.subjectspatiotemporal analysis-
dc.subjecturbanization stage-
dc.titleVariations in the Effects of Landscape Patterns on the Urban Thermal Environment during Rapid Urbanization (1990–2020) in Megacities-
dc.typeArticle-
dc.identifier.emailZheng, J: zhengji@hku.hk-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/rs13173415-
dc.identifier.scopuseid_2-s2.0-85114043311-
dc.identifier.hkuros328367-
dc.identifier.volume13-
dc.identifier.spagearticle no. 3415-
dc.identifier.epagearticle no. 3415-
dc.identifier.isiWOS:000694544800001-
dc.publisher.placeSwitzerland-

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